Three-way recommender systems based on random forests

•We propose a framework integrating three-way decision and random forests.•We introduce a new recommender action to consult the user for the choice.•We build a random forest to predict the probability that a user likes an item.•The three-way thresholds are optimal for both the training set and the testing set.